Precisely. The first 10 rungs of the ladder will be removed, but we still expect you to be able to get to the roof. The AI won't get you there and you won't have the knowledge you'd normally gain on those first 10 rungs to help you move past #10.

The correct distinction is: if you can't do something without the agent, then you can't do it.

The problem that the author describes is real. I have run into it hundreds of times now. I will know how to do something, I tell AI to do it, the AI does not actually know how to do it at a fundamental level and will create fake tests to prove that it is done, and you check the work and it is wrong.

You can describe to the AI to do X at a very high-level but if you don't know how to check the outcome then the AI isn't going to be useful.

The story about the cook is 100% right. McDonald's doesn't have "chefs", they have factory workers who assemble food. The argument with AI is that working in McDonald's means you are able to cook food as well as the best chef.

The issue with hiring is that companies won't be able to distinguish between AI-driven humans and people with knowledge until it is too late.

If you have knowledge and are using AI tools correctly (i.e. not trying to zero-shot work) then it is a huge multiplier. That the industry is moving towards agent-driven workflows indicates that the AI business is about selling fake expertise to the incompetent.

> The problem arrises when Bob encounters a problem too complex or unique for agents to solve.

It’s actually worse than that: the AI will not stop and say ”too complex, try in a month with the next SOTA model”. Rather, it will give Bob a plausible looking solution that Bob cannot identify as right or wrong. If Bob is working on an instant feedback problem, it’s ok: he can flag it, try again, ask for help. But if the error can’t be detected immediately, it can come back with a vengeance in a year. Perhaps Bob has already gotten promoted by then, and Bobs replacement gets to deal with it. In either case, Bob cannot be trusted any more than the LLM itself.

To me it feels more like learning to cook versus learning how to repair ovens and run a farm. Software engineering isn’t about writing code any more than it’s about writing machine code or designing CPUs. It’s about bringing great software into existence.

> The problem arrises when Bob encounters a problem too complex or unique for agents to solve.

Or even sooner, when Bob’s internet connection is down, or he ran out of tokens, or has been banned from his favourite service, or the service is down, or he needs to solve a problem with a machine unable to run local models, or essentially any situation where he’s unable to use an LLM.

That doesn't sound like much of an issue. Bob was already going to encounter problems that are too large and complex for him to solve, agents or otherwise. Life throws us hard problems. I don't recall if we even assumed Bob was unusually capable, he might be one of life's flounderers. I'd give good odds that if he got through a program with the help of agents he'll get through life achieving at least a normal level of success.

But there is also a more subtle thing, which is we're trending towards superintelligence with these AIs. At the point, Bob may discover that anything agents can't do, Alice can't do because she is limited by trying to think using soggy meat as opposed to a high-performance engineered thinking system. Not going to win that battle in the long term.

> The market will always value the exact things LLMs can not do, because if an LLM can do something, there is no reason to hire a person for that.

The market values bulldozers. Whether a human does actual work or not isn't particularly exciting to a market.

How many people who cook professionally are gourmet chefs? I think it ends up that gourmet cooking is so infrequently needed that we don’t require everyone who makes food to do it, just a small group of professionally trained people. Most people who make food for a living work somewhere like McDonald’s and Applebee’s where a high level of skill is not required.

There will still be programming specialists in the future — we still have assembly experts and COBOL experts, after all. We just won’t need very many of them and the vast majority of software engineers will use higher-level tools.

I held this point of view for a while but I came to the (possibly naive) conclusion that it was just forced self-assurance. Truth is, the issues with sub-par output are just a prompting and supervision deficiency. An agent team can produce better end product if supervised and promoted correctly. The issue is most don’t take the time to do that. I’m not saying I like that this is true, quite the opposite. It is the reality of things now.

Just because Bob doesn't know e.g. Rust syntax and library modules well, doesn't mean that Bob can't learn an algorithm to solve a difficult problem. The AI might suggest classes of algorithms that could be applicable given the real world constraints, and help Bob set up an experimental plan to test different algorithms for efficacy in the situation, but Bob's intuition is still in the drivers's seat.

Of course, that assumes a Bob with drive and agency. He could just as easily tell the AI to fix it without trying to stay in the loop.

Bob+agents is going to be able to solve much more complex problems than Bob without agents.

That's the true AI revolution: not the things it can accelerate, the things it can put in reach that you wouldn't countenance doing before.

Worse, soon fewer and fewer people will taste good food, including even higher and higher scale restaurants just using pre-made.

As fewer know what good food tastes like, the entire market will enshitify towards lower and lower calibre food.

We already see this with, for example, fruits in cold climates. I've known people who have only ever bought them from the supermarket, then tried them at a farmers when they're in season for 2 weeks. The look of astonishment on their faces, at the flavour, is quite telling. They simply had no idea how dry, flavourless supermarket fruit is.

Nothing beats an apple picked just before you eat it.

(For reference, produce shipped to supermarkets is often picked, even locally, before being entirely ripe. It last longer, and handles shipping better, than a perfectly ripe fruit.)

The same will be true of LLMs. They're already out of "new things" to train on. I question that they'll ever learn new languages, who will they observe to train on? What does it matter if the code is unreadable by humans regardless?

And this is the real danger. Eventually, we'll have entire coding languages that are just weird, incomprehensible, tailored to LLMs, maybe even a language written by an LLM.

What then? Who will be able to decipher such gibberish?

Literally all true advancement will stop, for LLMs never invent, they only mimic.

Real-world cooks don't exactly avoid those newfangled microwave ovens though. They use them as a professional tool for simple tasks where they're especially suitable (especially for quick defrosting or reheating), which sometimes allows them to cook even better meals.